scholarly journals An Evaluation of Project Risk Dynamics in Sino-Africa Public Infrastructure Delivery; A Causal Loop and Interpretive Structural Modelling Approach (ISM-CLD)

2021 ◽  
Vol 13 (19) ◽  
pp. 10822
Author(s):  
Bridget Tawiah Badu Eshun ◽  
Albert P.C. Chan

Africa’s growth in public infrastructure provision has been fueled by the collective effort of the government authority and foreign private investors. China, through state-owned corporations, has become one of the leading infrastructure financier springing up numerous projects in transport, energy, oil and gas, water, and sewage sectors in Africa. Infrastructure procurement in developing countries comes with complexities and uncertainties. While Sino-Africa transnational public–private partnerships (TPPP) are becoming an increasingly popular route for public infrastructure procurement, their specific project risks and dynamics are not yet fully understood due to the typical assessment of risk autonomously. This paper identifies pertinent project risks in Sino-Africa TPPPs and applies system thinking in evaluating their behaviour and dynamics. An extensive review of literature and expert opinion employing semi-structured interviews was adopted in the identification and assessment of risk factors. Additionally, the study applied causal loop and interpretive structural modelling as an integrated approach in the assessment of risk behaviour from a systems perspective. Results indicate that risk factors associated with Sino-Africa TPPPs are interactive and portray curious systemic behaviour. Risk factors like force majeure and others associated with the governance structure and stability of the host African country are most influential, and their occurrence could inhibit project success. The study recommends that in conjunction with the conventional risk assessment by impact, systems thinking can be adopted to evaluate and comprehend the dynamics and interactions amongst the risk factors. This will improve risk assessment efficiency and fair allocation and treatment of risks as a conduit for project success and promote a win–win partnership for project actors.

Author(s):  
Katarzyna Sienkiewicz-Małyjurek

AbstractInter-agency collaboration is a well-established, yet very difficult process in public governance. Despite the fact that it is often unsuccessful, collaboration risk research is still undeveloped and the impact of this risk on the effectiveness of joint activities is still underestimated. This issue is of particular significance in public safety networks, where inter-agency collaboration processes are conducted under the conditions of the complexity and uncertainty. For this reason, the article is intended to: (1) identify factors of collaboration risk in public safety networks, (2) determine the impact of individual risk factors on inter-agency collaboration outcomes, (3) identify the relationship between risk factors of inter-agency collaboration in public safety networks, and (4) analyse the growth of this risk in public safety networks. These purposes were achieved using the Systematic Literature Review based on PRISMA Group methodology and Interpretive Structural Modelling together with MICMAC analysis. The applied research approach also has some limitations resulting from the number of experts. However, the results obtained allow us to better understand issues of inter-agency collaboration risk in public safety networks. They identify key collaboration risk factors, such as inappropriate collaboration rules and inadequate allocation of tasks and resources. In consequence, they indicate risk symptoms that are worth keeping track of in order to prevent collaboration ineffectiveness.


2018 ◽  
Vol 7 (4-2) ◽  
pp. 247-260
Author(s):  
Chipo Mellania Maseko

Controlling project risks has become a daunting task in construction and this can be attributed to issues such as the nature of modern projects. The challenge is that risk appears unannounced at any project phase for various reasons and thereby affecting the performance and the success of unprepared projects. The current studies that explored risk matters include Pehlivan and Öztemir (2015), Katre, and Ghaitidak (2016) amongst others. However, there is absence of unanimity from these studies on risk factors in construction. Thus, this article was instigated in order to identify and classify risk factors that affect the chances of project success. The research methodology selected for this article comprised of peer-reviewed articles between the periods of 2007 to 2017. This approach involved a comprehensive scrutiny into scholarly articles to comprehend risks in construction projects. Following a conceptual analysis, eighty factors were identified and classified under the following; technical, construction, financial, socio-political, physical, organisational, and environmental and other risks. From these categories, political instability was, found to be the most influential risk factor in construction projects and this factor was classified within the socio-political category and this category has total of 11 factors. Finding suggests the need for further empirical study.


2016 ◽  
Vol 23 (1) ◽  
pp. 2-24 ◽  
Author(s):  
Chitrasen Samantra ◽  
Saurav Datta ◽  
Siba Sankar Mahapatra ◽  
Bikash Ranjan Debata

Purpose – Success of software projects depends on identification of project risks and managing the risks in a proactive manner. Risk management requires thorough insights into interrelationship of various risk factors for proposing strategies to minimize failure rate. The purpose of this paper is to develop a comprehensive structural model to interrelate important risk factors affecting the success of software projects. Design/methodology/approach – Specifically, this study reveals how interpretive structural modelling helps the risk managers in identifying and understanding the interrelationship among various risk factors. A total of 23 risk factors (or risk sources) have been identified through an extensive literature review. Findings – Necessary modelling information has been gathered from expert through a structured questionnaire survey. Matrice d’Impacts croises-multipication appliqué an classment analysis has been employed to classify the risk factors into four clusters such as autonomous, dependent, linkage and independent based on their driving and dependence power. Risk factors with strong dependence and weak driving power need urgent attention from managerial perspective. Originality/value – The proposed model is useful for software managers/practitioners to address risk factors associated with complicated projects.


2016 ◽  
Vol 34 (1) ◽  
pp. 42-53
Author(s):  
Kyung-Wan Seo ◽  
Jeong-Ok Lee ◽  
Sun-Young Choi ◽  
Min-Jung Park

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